Summary
Gaurav Rai is an AI Model Quality Analyst with 8 years of experience building production-grade ML systems that prioritize latency, scale, and model quality. He ships real-time pipelines, LLM integrations, and production APIs—recent contributions include a Weights & Biases GraphQL integration and substantial test-coverage improvements to the YC-backed Aden platform. His projects span recommender systems (BERT4Rec at sub-200ms latency for 51K articles), sub-100ms fraud detection inference pipelines, enterprise RAG platforms, and multimodal healthcare assistants on Hugging Face Spaces. Comfortable across Python, PyTorch, FastAPI, Spark, Azure, and vector databases like Pinecone, he combines research-level model work (multilingual NLI across 15 languages) with practical engineering for robust deployments. A Northeastern MS candidate and active open-source contributor based in Toronto, he seeks roles where messy, cross-cutting performance and quality trade-offs are central.
8 years of coding experience
2 years of employment as a software developer
Master of Science - MS, Information Systems, Master of Science - MS, Information Systems at Northeastern University
Bachelor of Engineering - BE, Computer Science, Bachelor of Engineering - BE, Computer Science at University of Mumbai